Назад
6 часов назад

Analytics Lead (AI)

160 000 - 240 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior/lead
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Analytics Lead (AI/Data): Building and optimizing AI-first analytics infrastructure and a single source of truth for business data with an accent on semantic layers, LLM tooling, and domain ontology. Focus on architecting demand/supply models and solving high-leverage data problems to empower cross-functional teams.

Location: Hybrid in Redwood City, CA (United States)

Salary: $160,000–$240,000

Company

Snorkel AI helps enterprises transform expert knowledge into specialized AI at scale by focusing on the high-performance data used to build production-ready systems.

What you will do

  • Build AI-first analytics infrastructure end-to-end, including semantic layers, LLM tooling, evals, and agents.
  • Define and implement taxonomy and domain ontology to match expert contributors to projects at scale.
  • Architect a demand and supply model to provide leadership with a forward-looking view of investments across domains and geographies.
  • Identify and prioritize high-leverage data opportunities to address business-limiting constraints.
  • Serve as a trusted thought partner on data architecture and analytics approach for operators, engineers, and executives.

Requirements

  • 5+ years of experience in analytics engineering, analytics, and data science.
  • Fluency in SQL and strong Python skills.
  • Hands-on experience with Snowflake and the modern data stack (e.g., dbt, Fivetran).
  • Practical experience with modern AI tooling, including LLMs, semantic layers, and eval frameworks.
  • Proven track record as a high-autonomy individual contributor in high-growth startup environments.
  • Must be based in the United States.

Nice to have

  • Experience with Streamlit or Snowflake Cortex.
  • Familiarity with AI/data labeling, DaaS, or marketplace business models.
  • Experience building BI infrastructure or semantic layers.
  • Experience with A/B testing in marketplace or workforce platform contexts.

Culture & Benefits

  • Equity compensation in the form of employee stock options.
  • Comprehensive benefits including medical, dental, vision, and 401(k).
  • Environment designed for high growth, continuous learning, and shared success.
  • High degree of ownership and autonomy in a senior individual contributor role.

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